1.Thin corpus callosum and"lynx ear sign":A report of a family of hereditary spastic paraplegia type 11
Zongyong YU ; Ziyang WU ; Feifei TIAN ; Jing LI ; Wei YUAN ; Xin LI ; Haiping WEI ; Guode WU ; Jun LIU
Chinese Journal of Nervous and Mental Diseases 2024;50(10):632-635
To report a case with hereditary spastic paraplegia type 11(SPG11)in association with typical thin corpus callosum(TCC)and"Ears-of-the-lynx sign"on MRI imaging.The patient was a 13-year-old boy.The main symptoms are walking instability and falling easily.Over the period of one year,the symptoms gradually progressed when accompanied by poor handwriting and a decrease in learning ability.The parents are not related.Brain MRI shows a thin corpus callosum,and high symmetric signals in the anterior horn of the lateral ventricles on T2 and Flair sequence.WES detected two heterozygous mutations in the SPG11 gene,NM_025137:c.2073delT and c.257+5G>A,respectively from the parents.The proband was finally diagnosed with SPG11.Brain MRI found that TCC and"lynx ear sign"are highly sensitive and specific for the diagnosis of SPG11.The patients with spastic paraplegia should be considered the possibility of SPG11.
2.Recent advance in predictors and risk prediction models for conversion from mild cognitive impairment to Alzheimer's disease
Yanru CHEN ; Hongxia LU ; Xinyu WANG ; Wenli SU ; Ya'nan HUANG ; Xiaoli CHEN ; Fanghong YAN ; Guode WU ; Lin HAN ; Yuxia MA
Chinese Journal of Neuromedicine 2022;21(6):629-635
Alzheimer's disease (AD) is the most common form of dementia in the elderly, and there is no specific treatment to stop or reverse its progression. Mild cognitive impairment (MCI) is an important entry point for early diagnosis and prevention of AD. More and more studies have explored the risk factors and biomarkers for conversion from MCI to AD, and a series of risk prediction models have been established. This article analyzes and summarizes the different predictors and risk prediction models so as to provide basis for early identifying the high-risk group of AD, managing the controllable risk factors, and providing references for the selection and improvement of these models.